ArticlemHealth2023
User-centered preferences for a gait-informed alcohol intoxication app.
Article in mHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Preferences for Mobile App Features to Support People Living With Chronic Heart Diseases: Discrete Choice Study.JMIR mHealth and uHealth · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Background: mHealth technology can be used as a potential intervention for alcohol-related consequences. Applications designed to monitor alcohol use and relay information to the user may help to reduce risky behavior. Acceptability of such applications needs to be assessed. Methods: Survey data from 139 participants (29.8 years on average, 58% female) completing a single-session study for developing an application to detect blood alcohol concentration (BAC) from gait was analyzed to examine user preferences. Participants reported on their interest in an application for monitoring BAC from gait. Participants also reported on their preference for controlling features of the application. Acceptability and feasibility data were collected. Data were examined for the entire sample as well as differences in preference by age and gender were examined. Results: The majority of the sample indicated that they were interested in using an mHealth application to infer BAC from their gait. Users were interested in being able to control features of the application, such as monitoring BAC and reporting information to other individuals. Adults, as compared to emerging adults, preferred the ability to turn off the BAC-monitoring feature of the app. Females reported a preference for an app that does not allow the user to turn off notifications for BAC as well as safety features of the app. Conclusions: Results of the survey data indicate general interest in mHealth technology that monitors BAC from passive input. These results suggest that such an app may be accepted and used as an intervention for monitoring alcohol levels, which could mediate drinking and alcohol-related consequences.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.